Machine Learning: How would it be if we could transfer repetitive and unproductive tasks to an intelligent computer system? That way, we could focus on more challenging work and add value to the business.
The problem is that such a solution does not exist. Correct? Not! Machine learning and the various artificial intelligence and data analysis tools can hand over most of the work to the machines themselves.
Thinking about talking more about the concept, its applications, and its many benefits, I prepared a private post on the subject. The subject has been much discussed lately, even due to the General Data Protection Law. Good reading!
After All, What Is Machine Learning?
Also known as machine learning, technology can be described as the ability to teach computers to think and act independently. In this way, the software can learn, through prescriptive data analysis, to present precise answers to some computational issues.
The concept seems quite far from the everyday application. Nothing further from the truth. This technology has already become standard in people’s routines — not just those who work with digital solutions.
So, when you do a Google search or accept a new movie suggestion on Netflix, you use a machine learning application directly. This is because technology makes it easier for the search engine to identify better results and even points out television attractions that may interest you based on your browsing history.
The main objective of this technology is to make machines able to make decisions without human interference. This becomes possible due to the algorithms (logical sequences of instructions passed on to the computer), which enable the computer system to identify patterns and point out appropriate solutions.
Unlike what happens with a joint program, a machine learning system can learn while performing the functions for which it was programmed. This feature makes it much more efficient compared to traditional software.
Connection With Artificial Intelligence
When reading about technology, people often come across concepts like machine learning being used interchangeably. This conception is partially correct, but it is simplistic: machine learning is one of the manifestations of AI.
In this sense, it joins other widely discussed technologies, such as Big Data, to enable practical applications of artificial intelligence.
Difference From Deep Learning
Similarly, deep learning is a way to put artificial intelligence to work. While machine learning works exclusively with structured data and requires the organization of this information, sophisticated deep-learning technology, and self-learning capabilities result in greater accuracy and faster processing.
Thus, machine learning has laid the foundations for deep learning to evolve, inheriting the main features of the traditional machine learning model and developing new features.
An exciting and recurring application of deep learning algorithms is optimized image recognition.
Why Invest In Machine Learning?
Now that we know the concept and its relationship with artificial intelligence and deep learning, it is time to learn about the advantages of investing in technology.
Background Knowledge For Decision Making
With an increasingly fierce market and the ease of customers finding new options, the most efficient managers must find differentiated strategies to identify new business opportunities.
Without this care, retaining consumers and winning over new customers becomes challenging to work. However, to develop strategies that allow more profitability, it is necessary to have accurate information. That’s where machine learning comes in.
That’s because every company generates a high load of data, especially with the internet guiding most of the business. With machine learning and data analysis tools, it will be possible to map the organization’s digital history, establish consumption patterns and generate new practical loyalty actions.
Machine learning studies information related to the business to trace consumption habits. It is possible to determine which products sell the most in a given period and anticipate this demand for the following year. The tool goes through the purchase history and offers valuable insights for the company.
Optimized Use Of Resources
A meaningful way to measure the success of an enterprise is to study how it directly allocates its physical and financial resources. A company that fails in this management tends to suffer continuous losses and show low overall productivity.
However, manually mapping all processes to identify failures and point out bottlenecks is exhausting for employees. It is necessary to appoint leaders and displace them from their usual functions, for example.
As if that needed to be more, every employee, no matter how talented they may be, can get complicated when dealing with a large amount of information. The company benefits from delivering purely manual jobs to machines by using machine learning solutions and automating some processes.
In addition to encouraging employees to dedicate themselves more to the company’s core activities, this digital solution also reduces rework, eliminating the risks associated with human errors.
Increased Profitability
Let’s assume that your company manages to commercialize a good amount of products annually. However, despite the numbers covering the losses, it has not grown significantly. That’s because daily activities make it difficult to identify new opportunities.
In this context, machine learning emerges as a tool capable of pointing out new paths for the organization. This is because technology contributes to the company being part of a data-driven culture — that is, one that uses Big Data and machine learning to find new ways to innovate.
The technology can analyze public databases such as government studies, social media, and information found on the internet to identify trends. This is especially important for finding gaps in the market and taking advantage of them to launch products accordingly, generating more profitability for the business.
Also Read: Machine Learning: The Technology Has So Much Potential In Production
